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<div class="title">GraphUtils.cpp</div>  </div>
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<a href="_graph_utils_8cpp.xhtml">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno">    1</span>&#160;<span class="comment">/*</span></div><div class="line"><a name="l00002"></a><span class="lineno">    2</span>&#160;<span class="comment"> * Copyright (c) 2017-2018 ARM Limited.</span></div><div class="line"><a name="l00003"></a><span class="lineno">    3</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00004"></a><span class="lineno">    4</span>&#160;<span class="comment"> * SPDX-License-Identifier: MIT</span></div><div class="line"><a name="l00005"></a><span class="lineno">    5</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00006"></a><span class="lineno">    6</span>&#160;<span class="comment"> * Permission is hereby granted, free of charge, to any person obtaining a copy</span></div><div class="line"><a name="l00007"></a><span class="lineno">    7</span>&#160;<span class="comment"> * of this software and associated documentation files (the &quot;Software&quot;), to</span></div><div class="line"><a name="l00008"></a><span class="lineno">    8</span>&#160;<span class="comment"> * deal in the Software without restriction, including without limitation the</span></div><div class="line"><a name="l00009"></a><span class="lineno">    9</span>&#160;<span class="comment"> * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or</span></div><div class="line"><a name="l00010"></a><span class="lineno">   10</span>&#160;<span class="comment"> * sell copies of the Software, and to permit persons to whom the Software is</span></div><div class="line"><a name="l00011"></a><span class="lineno">   11</span>&#160;<span class="comment"> * furnished to do so, subject to the following conditions:</span></div><div class="line"><a name="l00012"></a><span class="lineno">   12</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00013"></a><span class="lineno">   13</span>&#160;<span class="comment"> * The above copyright notice and this permission notice shall be included in all</span></div><div class="line"><a name="l00014"></a><span class="lineno">   14</span>&#160;<span class="comment"> * copies or substantial portions of the Software.</span></div><div class="line"><a name="l00015"></a><span class="lineno">   15</span>&#160;<span class="comment"> *</span></div><div class="line"><a name="l00016"></a><span class="lineno">   16</span>&#160;<span class="comment"> * THE SOFTWARE IS PROVIDED &quot;AS IS&quot;, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR</span></div><div class="line"><a name="l00017"></a><span class="lineno">   17</span>&#160;<span class="comment"> * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,</span></div><div class="line"><a name="l00018"></a><span class="lineno">   18</span>&#160;<span class="comment"> * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE</span></div><div class="line"><a name="l00019"></a><span class="lineno">   19</span>&#160;<span class="comment"> * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER</span></div><div class="line"><a name="l00020"></a><span class="lineno">   20</span>&#160;<span class="comment"> * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,</span></div><div class="line"><a name="l00021"></a><span class="lineno">   21</span>&#160;<span class="comment"> * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE</span></div><div class="line"><a name="l00022"></a><span class="lineno">   22</span>&#160;<span class="comment"> * SOFTWARE.</span></div><div class="line"><a name="l00023"></a><span class="lineno">   23</span>&#160;<span class="comment"> */</span></div><div class="line"><a name="l00024"></a><span class="lineno">   24</span>&#160;</div><div class="line"><a name="l00025"></a><span class="lineno">   25</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_graph_utils_8h.xhtml">utils/GraphUtils.h</a>&quot;</span></div><div class="line"><a name="l00026"></a><span class="lineno">   26</span>&#160;</div><div class="line"><a name="l00027"></a><span class="lineno">   27</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="runtime_2_sub_tensor_8h.xhtml">arm_compute/runtime/SubTensor.h</a>&quot;</span></div><div class="line"><a name="l00028"></a><span class="lineno">   28</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="utils_2_utils_8h.xhtml">utils/Utils.h</a>&quot;</span></div><div class="line"><a name="l00029"></a><span class="lineno">   29</span>&#160;</div><div class="line"><a name="l00030"></a><span class="lineno">   30</span>&#160;<span class="preprocessor">#ifdef ARM_COMPUTE_CL</span></div><div class="line"><a name="l00031"></a><span class="lineno">   31</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_open_c_l_8h.xhtml">arm_compute/core/CL/OpenCL.h</a>&quot;</span></div><div class="line"><a name="l00032"></a><span class="lineno">   32</span>&#160;<span class="preprocessor">#include &quot;<a class="code" href="_c_l_tensor_8h.xhtml">arm_compute/runtime/CL/CLTensor.h</a>&quot;</span></div><div class="line"><a name="l00033"></a><span class="lineno">   33</span>&#160;<span class="preprocessor">#endif </span><span class="comment">/* ARM_COMPUTE_CL */</span><span class="preprocessor"></span></div><div class="line"><a name="l00034"></a><span class="lineno">   34</span>&#160;</div><div class="line"><a name="l00035"></a><span class="lineno">   35</span>&#160;<span class="preprocessor">#include &lt;iomanip&gt;</span></div><div class="line"><a name="l00036"></a><span class="lineno">   36</span>&#160;</div><div class="line"><a name="l00037"></a><span class="lineno">   37</span>&#160;<span class="keyword">using namespace </span><a class="code" href="namespacearm__compute_1_1graph__utils.xhtml">arm_compute::graph_utils</a>;</div><div class="line"><a name="l00038"></a><span class="lineno">   38</span>&#160;</div><div class="line"><a name="l00039"></a><span class="lineno"><a class="line" href="classarm__compute_1_1graph__utils_1_1_t_f_preproccessor.xhtml#a1545d087d050b8e9733e7e212df73666">   39</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1graph__utils_1_1_t_f_preproccessor.xhtml#a1545d087d050b8e9733e7e212df73666">TFPreproccessor::preprocess</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> &amp;tensor)</div><div class="line"><a name="l00040"></a><span class="lineno">   40</span>&#160;{</div><div class="line"><a name="l00041"></a><span class="lineno">   41</span>&#160;    <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> window;</div><div class="line"><a name="l00042"></a><span class="lineno">   42</span>&#160;    window.<a class="code" href="classarm__compute_1_1_window.xhtml#a14470b4cb59140a1b6ff3b8f16c89ab6">use_tensor_dimensions</a>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>());</div><div class="line"><a name="l00043"></a><span class="lineno">   43</span>&#160;</div><div class="line"><a name="l00044"></a><span class="lineno">   44</span>&#160;    <a class="code" href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">execute_window_loop</a>(window, [&amp;](<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &amp; <span class="keywordtype">id</span>)</div><div class="line"><a name="l00045"></a><span class="lineno">   45</span>&#160;    {</div><div class="line"><a name="l00046"></a><span class="lineno">   46</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">float</span> <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>                                     = *<span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">float</span> *<span class="keyword">&gt;</span>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a48c7a05cc63f541d732250e39339cee2">ptr_to_element</a>(<span class="keywordtype">id</span>));</div><div class="line"><a name="l00047"></a><span class="lineno">   47</span>&#160;        <span class="keywordtype">float</span>       res                                       = value / 255.f;      <span class="comment">// Normalize to [0, 1]</span></div><div class="line"><a name="l00048"></a><span class="lineno">   48</span>&#160;        res                                                   = (res - 0.5f) * 2.f; <span class="comment">// Map to [-1, 1]</span></div><div class="line"><a name="l00049"></a><span class="lineno">   49</span>&#160;        *<span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">float</span> *<span class="keyword">&gt;</span>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a48c7a05cc63f541d732250e39339cee2">ptr_to_element</a>(<span class="keywordtype">id</span>)) = res;</div><div class="line"><a name="l00050"></a><span class="lineno">   50</span>&#160;    });</div><div class="line"><a name="l00051"></a><span class="lineno">   51</span>&#160;}</div><div class="line"><a name="l00052"></a><span class="lineno">   52</span>&#160;</div><div class="line"><a name="l00053"></a><span class="lineno"><a class="line" href="classarm__compute_1_1graph__utils_1_1_caffe_preproccessor.xhtml#a60e1354276a6ffd7359634e1ab464cff">   53</a></span>&#160;<a class="code" href="classarm__compute_1_1graph__utils_1_1_caffe_preproccessor.xhtml#a60e1354276a6ffd7359634e1ab464cff">CaffePreproccessor::CaffePreproccessor</a>(std::array&lt;float, 3&gt; mean, <span class="keywordtype">bool</span> bgr)</div><div class="line"><a name="l00054"></a><span class="lineno">   54</span>&#160;    : _mean(mean), _bgr(bgr)</div><div class="line"><a name="l00055"></a><span class="lineno">   55</span>&#160;{</div><div class="line"><a name="l00056"></a><span class="lineno">   56</span>&#160;    <span class="keywordflow">if</span>(_bgr)</div><div class="line"><a name="l00057"></a><span class="lineno">   57</span>&#160;    {</div><div class="line"><a name="l00058"></a><span class="lineno">   58</span>&#160;        <a class="code" href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">std::swap</a>(_mean[0], _mean[2]);</div><div class="line"><a name="l00059"></a><span class="lineno">   59</span>&#160;    }</div><div class="line"><a name="l00060"></a><span class="lineno">   60</span>&#160;}</div><div class="line"><a name="l00061"></a><span class="lineno">   61</span>&#160;</div><div class="line"><a name="l00062"></a><span class="lineno"><a class="line" href="classarm__compute_1_1graph__utils_1_1_caffe_preproccessor.xhtml#a1545d087d050b8e9733e7e212df73666">   62</a></span>&#160;<span class="keywordtype">void</span> <a class="code" href="classarm__compute_1_1graph__utils_1_1_caffe_preproccessor.xhtml#a1545d087d050b8e9733e7e212df73666">CaffePreproccessor::preprocess</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> &amp;tensor)</div><div class="line"><a name="l00063"></a><span class="lineno">   63</span>&#160;{</div><div class="line"><a name="l00064"></a><span class="lineno">   64</span>&#160;    <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> window;</div><div class="line"><a name="l00065"></a><span class="lineno">   65</span>&#160;    window.<a class="code" href="classarm__compute_1_1_window.xhtml#a14470b4cb59140a1b6ff3b8f16c89ab6">use_tensor_dimensions</a>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>());</div><div class="line"><a name="l00066"></a><span class="lineno">   66</span>&#160;</div><div class="line"><a name="l00067"></a><span class="lineno">   67</span>&#160;    <a class="code" href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">execute_window_loop</a>(window, [&amp;](<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &amp; <span class="keywordtype">id</span>)</div><div class="line"><a name="l00068"></a><span class="lineno">   68</span>&#160;    {</div><div class="line"><a name="l00069"></a><span class="lineno">   69</span>&#160;        <span class="keyword">const</span> <span class="keywordtype">float</span> <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>                                     = *<span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">float</span> *<span class="keyword">&gt;</span>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a48c7a05cc63f541d732250e39339cee2">ptr_to_element</a>(<span class="keywordtype">id</span>)) - _mean[<span class="keywordtype">id</span>.z()];</div><div class="line"><a name="l00070"></a><span class="lineno">   70</span>&#160;        *<span class="keyword">reinterpret_cast&lt;</span><span class="keywordtype">float</span> *<span class="keyword">&gt;</span>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a48c7a05cc63f541d732250e39339cee2">ptr_to_element</a>(<span class="keywordtype">id</span>)) = value;</div><div class="line"><a name="l00071"></a><span class="lineno">   71</span>&#160;    });</div><div class="line"><a name="l00072"></a><span class="lineno">   72</span>&#160;}</div><div class="line"><a name="l00073"></a><span class="lineno">   73</span>&#160;</div><div class="line"><a name="l00074"></a><span class="lineno"><a class="line" href="classarm__compute_1_1graph__utils_1_1_p_p_m_writer.xhtml#a9ea94bf5b7d00ddb836df1b8dcedb93a">   74</a></span>&#160;<a class="code" href="classarm__compute_1_1graph__utils_1_1_p_p_m_writer.xhtml#a9ea94bf5b7d00ddb836df1b8dcedb93a">PPMWriter::PPMWriter</a>(std::string name, <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span> maximum)</div><div class="line"><a name="l00075"></a><span class="lineno">   75</span>&#160;    : _name(std::move(name)), _iterator(0), _maximum(maximum)</div><div class="line"><a name="l00076"></a><span class="lineno">   76</span>&#160;{</div><div class="line"><a name="l00077"></a><span class="lineno">   77</span>&#160;}</div><div class="line"><a name="l00078"></a><span class="lineno">   78</span>&#160;</div><div class="line"><a name="l00079"></a><span class="lineno"><a class="line" href="classarm__compute_1_1graph__utils_1_1_p_p_m_writer.xhtml#ab469d593b4bc92e1d1132a03de0aedca">   79</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1graph__utils_1_1_p_p_m_writer.xhtml#ab469d593b4bc92e1d1132a03de0aedca">PPMWriter::access_tensor</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> &amp;tensor)</div><div class="line"><a name="l00080"></a><span class="lineno">   80</span>&#160;{</div><div class="line"><a name="l00081"></a><span class="lineno">   81</span>&#160;    std::stringstream ss;</div><div class="line"><a name="l00082"></a><span class="lineno">   82</span>&#160;    ss &lt;&lt; _name &lt;&lt; _iterator &lt;&lt; <span class="stringliteral">&quot;.ppm&quot;</span>;</div><div class="line"><a name="l00083"></a><span class="lineno">   83</span>&#160;</div><div class="line"><a name="l00084"></a><span class="lineno">   84</span>&#160;    <a class="code" href="namespacearm__compute_1_1utils.xhtml#a301d0b7bfd70f73fc1924f4281938d08">arm_compute::utils::save_to_ppm</a>(tensor, ss.str());</div><div class="line"><a name="l00085"></a><span class="lineno">   85</span>&#160;</div><div class="line"><a name="l00086"></a><span class="lineno">   86</span>&#160;    _iterator++;</div><div class="line"><a name="l00087"></a><span class="lineno">   87</span>&#160;    <span class="keywordflow">if</span>(_maximum == 0)</div><div class="line"><a name="l00088"></a><span class="lineno">   88</span>&#160;    {</div><div class="line"><a name="l00089"></a><span class="lineno">   89</span>&#160; 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                            <span class="stringliteral">&quot;Failed to load image file: dimensions [%d,%d] not correct, expected [%d,%d].&quot;</span>, ppm.<a class="code" href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a7b736ec9a05be5c498760d35a0406ed3">width</a>(), ppm.<a class="code" href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#aa420a28166e708e3f8b9ecc8e527fc09">height</a>(), tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(0), tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(1));</div><div class="line"><a name="l00128"></a><span class="lineno">  128</span>&#160;</div><div class="line"><a name="l00129"></a><span class="lineno">  129</span>&#160; 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   <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00139"></a><span class="lineno">  139</span>&#160;}</div><div class="line"><a name="l00140"></a><span class="lineno">  140</span>&#160;</div><div class="line"><a name="l00141"></a><span class="lineno"><a class="line" href="classarm__compute_1_1graph__utils_1_1_top_n_predictions_accessor.xhtml#ad12f4e3c945ec4fad9ab6386954a3550">  141</a></span>&#160;<a class="code" href="classarm__compute_1_1graph__utils_1_1_top_n_predictions_accessor.xhtml#ad12f4e3c945ec4fad9ab6386954a3550">TopNPredictionsAccessor::TopNPredictionsAccessor</a>(<span class="keyword">const</span> std::string &amp;labels_path, <span class="keywordtype">size_t</span> top_n, std::ostream &amp;output_stream)</div><div class="line"><a name="l00142"></a><span class="lineno">  142</span>&#160;    : _labels(), _output_stream(output_stream), _top_n(top_n)</div><div class="line"><a name="l00143"></a><span class="lineno">  143</span>&#160;{</div><div class="line"><a name="l00144"></a><span class="lineno">  144</span>&#160;    _labels.clear();</div><div class="line"><a name="l00145"></a><span class="lineno">  145</span>&#160;</div><div class="line"><a name="l00146"></a><span class="lineno">  146</span>&#160;    std::ifstream ifs;</div><div class="line"><a name="l00147"></a><span class="lineno">  147</span>&#160;</div><div class="line"><a name="l00148"></a><span class="lineno">  148</span>&#160;    <span class="keywordflow">try</span></div><div class="line"><a name="l00149"></a><span class="lineno">  149</span>&#160;    {</div><div class="line"><a name="l00150"></a><span class="lineno">  150</span>&#160;        ifs.exceptions(std::ifstream::badbit);</div><div class="line"><a name="l00151"></a><span class="lineno">  151</span>&#160;        ifs.open(labels_path, std::ios::in | std::ios::binary);</div><div class="line"><a name="l00152"></a><span class="lineno">  152</span>&#160;</div><div class="line"><a name="l00153"></a><span class="lineno">  153</span>&#160;        <span class="keywordflow">for</span>(std::string line; 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   }</div><div class="line"><a name="l00196"></a><span class="lineno">  196</span>&#160;}</div><div class="line"><a name="l00197"></a><span class="lineno">  197</span>&#160;</div><div class="line"><a name="l00198"></a><span class="lineno"><a class="line" href="classarm__compute_1_1graph__utils_1_1_top_n_predictions_accessor.xhtml#ab469d593b4bc92e1d1132a03de0aedca">  198</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1graph__utils_1_1_top_n_predictions_accessor.xhtml#ab469d593b4bc92e1d1132a03de0aedca">TopNPredictionsAccessor::access_tensor</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> &amp;tensor)</div><div class="line"><a name="l00199"></a><span class="lineno">  199</span>&#160;{</div><div class="line"><a name="l00200"></a><span class="lineno">  200</span>&#160;    <a class="code" href="_validate_8h.xhtml#aadf5c9cff86327b96d88d04649d9715e">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a>(&amp;tensor, 1, <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>, <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>);</div><div class="line"><a name="l00201"></a><span class="lineno">  201</span>&#160;    <a class="code" href="core_2_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a>(_labels.size() != tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">dimension</a>(0));</div><div class="line"><a name="l00202"></a><span class="lineno">  202</span>&#160;</div><div class="line"><a name="l00203"></a><span class="lineno">  203</span>&#160;    <span class="keywordflow">switch</span>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>())</div><div class="line"><a name="l00204"></a><span class="lineno">  204</span>&#160;    {</div><div class="line"><a name="l00205"></a><span class="lineno">  205</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">DataType::QASYMM8</a>:</div><div class="line"><a name="l00206"></a><span class="lineno">  206</span>&#160;            access_predictions_tensor&lt;uint8_t&gt;(tensor);</div><div class="line"><a name="l00207"></a><span class="lineno">  207</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00208"></a><span class="lineno">  208</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>:</div><div class="line"><a name="l00209"></a><span class="lineno">  209</span>&#160;            access_predictions_tensor&lt;float&gt;(tensor);</div><div class="line"><a name="l00210"></a><span class="lineno">  210</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00211"></a><span class="lineno">  211</span>&#160;        <span class="keywordflow">default</span>:</div><div class="line"><a name="l00212"></a><span class="lineno">  212</span>&#160;            <a class="code" href="core_2_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">&quot;NOT SUPPORTED!&quot;</span>);</div><div class="line"><a name="l00213"></a><span class="lineno">  213</span>&#160;    }</div><div class="line"><a name="l00214"></a><span class="lineno">  214</span>&#160;</div><div class="line"><a name="l00215"></a><span class="lineno">  215</span>&#160;    <span class="keywordflow">return</span> <span class="keyword">false</span>;</div><div class="line"><a name="l00216"></a><span class="lineno">  216</span>&#160;}</div><div class="line"><a name="l00217"></a><span class="lineno">  217</span>&#160;</div><div class="line"><a name="l00218"></a><span class="lineno"><a class="line" href="classarm__compute_1_1graph__utils_1_1_random_accessor.xhtml#a47e2e3f731e842dde7baaf69634a9530">  218</a></span>&#160;<a class="code" href="classarm__compute_1_1graph__utils_1_1_random_accessor.xhtml#a47e2e3f731e842dde7baaf69634a9530">RandomAccessor::RandomAccessor</a>(<a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a> lower, <a class="code" href="classarm__compute_1_1_pixel_value.xhtml">PixelValue</a> upper, std::random_device::result_type seed)</div><div class="line"><a name="l00219"></a><span class="lineno">  219</span>&#160;    : _lower(lower), _upper(upper), _seed(seed)</div><div class="line"><a name="l00220"></a><span class="lineno">  220</span>&#160;{</div><div class="line"><a name="l00221"></a><span class="lineno">  221</span>&#160;}</div><div class="line"><a name="l00222"></a><span class="lineno">  222</span>&#160;</div><div class="line"><a name="l00223"></a><span class="lineno">  223</span>&#160;<span class="keyword">template</span> &lt;<span class="keyword">typename</span> T, <span class="keyword">typename</span> D&gt;</div><div class="line"><a name="l00224"></a><span class="lineno">  224</span>&#160;<span class="keywordtype">void</span> RandomAccessor::fill(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> &amp;tensor, D &amp;&amp;distribution)</div><div class="line"><a name="l00225"></a><span class="lineno">  225</span>&#160;{</div><div class="line"><a name="l00226"></a><span class="lineno">  226</span>&#160;    std::mt19937 gen(_seed);</div><div class="line"><a name="l00227"></a><span class="lineno">  227</span>&#160;</div><div class="line"><a name="l00228"></a><span class="lineno">  228</span>&#160;    <span class="keywordflow">if</span>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a07b929c34ad1dc823d8315876aa403ce">padding</a>().<a class="code" href="structarm__compute_1_1_border_size.xhtml#adffbf97e7b8b64e7cf32f0254cddf3c4">empty</a>() &amp;&amp; (<span class="keyword">dynamic_cast&lt;</span><a class="code" href="classarm__compute_1_1_sub_tensor.xhtml">SubTensor</a> *<span class="keyword">&gt;</span>(&amp;tensor) == <span class="keyword">nullptr</span>))</div><div class="line"><a name="l00229"></a><span class="lineno">  229</span>&#160;    {</div><div class="line"><a name="l00230"></a><span class="lineno">  230</span>&#160;        <span class="keywordflow">for</span>(<span class="keywordtype">size_t</span> <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> = 0; <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> &lt; tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">total_size</a>(); <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a> += tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#aa459796b5489eca8a9160cb5dcf1a103">element_size</a>())</div><div class="line"><a name="l00231"></a><span class="lineno">  231</span>&#160;        {</div><div class="line"><a name="l00232"></a><span class="lineno">  232</span>&#160;            <span class="keyword">const</span> T <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>                                    = distribution(gen);</div><div class="line"><a name="l00233"></a><span class="lineno">  233</span>&#160;            *<span class="keyword">reinterpret_cast&lt;</span>T *<span class="keyword">&gt;</span>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#ab988210662dbd3bf32fd563c7dd1bdbf">buffer</a>() + <a class="code" href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a>) = value;</div><div class="line"><a name="l00234"></a><span class="lineno">  234</span>&#160;        }</div><div class="line"><a name="l00235"></a><span class="lineno">  235</span>&#160;    }</div><div class="line"><a name="l00236"></a><span class="lineno">  236</span>&#160;    <span class="keywordflow">else</span></div><div class="line"><a name="l00237"></a><span class="lineno">  237</span>&#160;    {</div><div class="line"><a name="l00238"></a><span class="lineno">  238</span>&#160;        <span class="comment">// If tensor has padding accessing tensor elements through execution window.</span></div><div class="line"><a name="l00239"></a><span class="lineno">  239</span>&#160;        <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> window;</div><div class="line"><a name="l00240"></a><span class="lineno">  240</span>&#160;        window.<a class="code" href="classarm__compute_1_1_window.xhtml#a14470b4cb59140a1b6ff3b8f16c89ab6">use_tensor_dimensions</a>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>());</div><div class="line"><a name="l00241"></a><span class="lineno">  241</span>&#160;</div><div class="line"><a name="l00242"></a><span class="lineno">  242</span>&#160;        <a class="code" href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">execute_window_loop</a>(window, [&amp;](<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &amp; <span class="keywordtype">id</span>)</div><div class="line"><a name="l00243"></a><span class="lineno">  243</span>&#160;        {</div><div class="line"><a name="l00244"></a><span class="lineno">  244</span>&#160;            <span class="keyword">const</span> T <a class="code" href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a>                                     = distribution(gen);</div><div class="line"><a name="l00245"></a><span class="lineno">  245</span>&#160;            *<span class="keyword">reinterpret_cast&lt;</span>T *<span class="keyword">&gt;</span>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a48c7a05cc63f541d732250e39339cee2">ptr_to_element</a>(<span class="keywordtype">id</span>)) = value;</div><div class="line"><a name="l00246"></a><span class="lineno">  246</span>&#160;        });</div><div class="line"><a name="l00247"></a><span class="lineno">  247</span>&#160;    }</div><div class="line"><a name="l00248"></a><span class="lineno">  248</span>&#160;}</div><div class="line"><a name="l00249"></a><span class="lineno">  249</span>&#160;</div><div class="line"><a name="l00250"></a><span class="lineno"><a class="line" href="classarm__compute_1_1graph__utils_1_1_random_accessor.xhtml#ab469d593b4bc92e1d1132a03de0aedca">  250</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1graph__utils_1_1_random_accessor.xhtml#ab469d593b4bc92e1d1132a03de0aedca">RandomAccessor::access_tensor</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> &amp;tensor)</div><div class="line"><a name="l00251"></a><span class="lineno">  251</span>&#160;{</div><div class="line"><a name="l00252"></a><span class="lineno">  252</span>&#160;    <span class="keywordflow">switch</span>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>())</div><div class="line"><a name="l00253"></a><span class="lineno">  253</span>&#160;    {</div><div class="line"><a name="l00254"></a><span class="lineno">  254</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">DataType::U8</a>:</div><div class="line"><a name="l00255"></a><span class="lineno">  255</span>&#160;        {</div><div class="line"><a name="l00256"></a><span class="lineno">  256</span>&#160;            std::uniform_int_distribution&lt;uint8_t&gt; distribution_u8(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;uint8_t&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;uint8_t&gt;());</div><div class="line"><a name="l00257"></a><span class="lineno">  257</span>&#160;            fill&lt;uint8_t&gt;(tensor, distribution_u8);</div><div class="line"><a name="l00258"></a><span class="lineno">  258</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00259"></a><span class="lineno">  259</span>&#160;        }</div><div class="line"><a name="l00260"></a><span class="lineno">  260</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975">DataType::S8</a>:</div><div class="line"><a name="l00261"></a><span class="lineno">  261</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a11cde4d3551db3f9498d339a67189543">DataType::QS8</a>:</div><div class="line"><a name="l00262"></a><span class="lineno">  262</span>&#160;        {</div><div class="line"><a name="l00263"></a><span class="lineno">  263</span>&#160;            std::uniform_int_distribution&lt;int8_t&gt; distribution_s8(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;int8_t&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;int8_t&gt;());</div><div class="line"><a name="l00264"></a><span class="lineno">  264</span>&#160;            fill&lt;int8_t&gt;(tensor, distribution_s8);</div><div class="line"><a name="l00265"></a><span class="lineno">  265</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00266"></a><span class="lineno">  266</span>&#160;        }</div><div class="line"><a name="l00267"></a><span class="lineno">  267</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">DataType::U16</a>:</div><div class="line"><a name="l00268"></a><span class="lineno">  268</span>&#160;        {</div><div class="line"><a name="l00269"></a><span class="lineno">  269</span>&#160;            std::uniform_int_distribution&lt;uint16_t&gt; distribution_u16(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;uint16_t&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;uint16_t&gt;());</div><div class="line"><a name="l00270"></a><span class="lineno">  270</span>&#160;            fill&lt;uint16_t&gt;(tensor, distribution_u16);</div><div class="line"><a name="l00271"></a><span class="lineno">  271</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00272"></a><span class="lineno">  272</span>&#160;        }</div><div class="line"><a name="l00273"></a><span class="lineno">  273</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">DataType::S16</a>:</div><div class="line"><a name="l00274"></a><span class="lineno">  274</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a48d877702a2957f5a932c43a357866f9">DataType::QS16</a>:</div><div class="line"><a name="l00275"></a><span class="lineno">  275</span>&#160;        {</div><div class="line"><a name="l00276"></a><span class="lineno">  276</span>&#160;            std::uniform_int_distribution&lt;int16_t&gt; distribution_s16(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;int16_t&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;int16_t&gt;());</div><div class="line"><a name="l00277"></a><span class="lineno">  277</span>&#160;            fill&lt;int16_t&gt;(tensor, distribution_s16);</div><div class="line"><a name="l00278"></a><span class="lineno">  278</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00279"></a><span class="lineno">  279</span>&#160;        }</div><div class="line"><a name="l00280"></a><span class="lineno">  280</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">DataType::U32</a>:</div><div class="line"><a name="l00281"></a><span class="lineno">  281</span>&#160;        {</div><div class="line"><a name="l00282"></a><span class="lineno">  282</span>&#160;            std::uniform_int_distribution&lt;uint32_t&gt; distribution_u32(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;uint32_t&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;uint32_t&gt;());</div><div class="line"><a name="l00283"></a><span class="lineno">  283</span>&#160;            fill&lt;uint32_t&gt;(tensor, distribution_u32);</div><div class="line"><a name="l00284"></a><span class="lineno">  284</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00285"></a><span class="lineno">  285</span>&#160;        }</div><div class="line"><a name="l00286"></a><span class="lineno">  286</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">DataType::S32</a>:</div><div class="line"><a name="l00287"></a><span class="lineno">  287</span>&#160;        {</div><div class="line"><a name="l00288"></a><span class="lineno">  288</span>&#160;            std::uniform_int_distribution&lt;int32_t&gt; distribution_s32(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;int32_t&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;int32_t&gt;());</div><div class="line"><a name="l00289"></a><span class="lineno">  289</span>&#160;            fill&lt;int32_t&gt;(tensor, distribution_s32);</div><div class="line"><a name="l00290"></a><span class="lineno">  290</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00291"></a><span class="lineno">  291</span>&#160;        }</div><div class="line"><a name="l00292"></a><span class="lineno">  292</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a31d65cccd6593e4101db93fb878abcaa">DataType::U64</a>:</div><div class="line"><a name="l00293"></a><span class="lineno">  293</span>&#160;        {</div><div class="line"><a name="l00294"></a><span class="lineno">  294</span>&#160;            std::uniform_int_distribution&lt;uint64_t&gt; distribution_u64(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;uint64_t&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;uint64_t&gt;());</div><div class="line"><a name="l00295"></a><span class="lineno">  295</span>&#160;            fill&lt;uint64_t&gt;(tensor, distribution_u64);</div><div class="line"><a name="l00296"></a><span class="lineno">  296</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00297"></a><span class="lineno">  297</span>&#160;        }</div><div class="line"><a name="l00298"></a><span class="lineno">  298</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a115dca124dc6423c7a400b8a8a0270cc">DataType::S64</a>:</div><div class="line"><a name="l00299"></a><span class="lineno">  299</span>&#160;        {</div><div class="line"><a name="l00300"></a><span class="lineno">  300</span>&#160;            std::uniform_int_distribution&lt;int64_t&gt; distribution_s64(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;int64_t&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;int64_t&gt;());</div><div class="line"><a name="l00301"></a><span class="lineno">  301</span>&#160;            fill&lt;int64_t&gt;(tensor, distribution_s64);</div><div class="line"><a name="l00302"></a><span class="lineno">  302</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00303"></a><span class="lineno">  303</span>&#160;        }</div><div class="line"><a name="l00304"></a><span class="lineno">  304</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">DataType::F16</a>:</div><div class="line"><a name="l00305"></a><span class="lineno">  305</span>&#160;        {</div><div class="line"><a name="l00306"></a><span class="lineno">  306</span>&#160;            std::uniform_real_distribution&lt;float&gt; distribution_f16(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;<span class="keywordtype">float</span>&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;<span class="keywordtype">float</span>&gt;());</div><div class="line"><a name="l00307"></a><span class="lineno">  307</span>&#160;            fill&lt;float&gt;(tensor, distribution_f16);</div><div class="line"><a name="l00308"></a><span class="lineno">  308</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00309"></a><span class="lineno">  309</span>&#160;        }</div><div class="line"><a name="l00310"></a><span class="lineno">  310</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">DataType::F32</a>:</div><div class="line"><a name="l00311"></a><span class="lineno">  311</span>&#160;        {</div><div class="line"><a name="l00312"></a><span class="lineno">  312</span>&#160;            std::uniform_real_distribution&lt;float&gt; distribution_f32(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;<span class="keywordtype">float</span>&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;<span class="keywordtype">float</span>&gt;());</div><div class="line"><a name="l00313"></a><span class="lineno">  313</span>&#160;            fill&lt;float&gt;(tensor, distribution_f32);</div><div class="line"><a name="l00314"></a><span class="lineno">  314</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00315"></a><span class="lineno">  315</span>&#160;        }</div><div class="line"><a name="l00316"></a><span class="lineno">  316</span>&#160;        <span class="keywordflow">case</span> <a class="code" href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a1ad5f6f3069070ec4cbbdc94d5e61e0e">DataType::F64</a>:</div><div class="line"><a name="l00317"></a><span class="lineno">  317</span>&#160;        {</div><div class="line"><a name="l00318"></a><span class="lineno">  318</span>&#160;            std::uniform_real_distribution&lt;double&gt; distribution_f64(_lower.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;<span class="keywordtype">double</span>&gt;(), _upper.<a class="code" href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">get</a>&lt;<span class="keywordtype">double</span>&gt;());</div><div class="line"><a name="l00319"></a><span class="lineno">  319</span>&#160;            fill&lt;double&gt;(tensor, distribution_f64);</div><div class="line"><a name="l00320"></a><span class="lineno">  320</span>&#160;            <span class="keywordflow">break</span>;</div><div class="line"><a name="l00321"></a><span class="lineno">  321</span>&#160;        }</div><div class="line"><a name="l00322"></a><span class="lineno">  322</span>&#160;        <span class="keywordflow">default</span>:</div><div class="line"><a name="l00323"></a><span class="lineno">  323</span>&#160;            <a class="code" href="core_2_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a>(<span class="stringliteral">&quot;NOT SUPPORTED!&quot;</span>);</div><div class="line"><a name="l00324"></a><span class="lineno">  324</span>&#160;    }</div><div class="line"><a name="l00325"></a><span class="lineno">  325</span>&#160;    <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00326"></a><span class="lineno">  326</span>&#160;}</div><div class="line"><a name="l00327"></a><span class="lineno">  327</span>&#160;</div><div class="line"><a name="l00328"></a><span class="lineno"><a class="line" href="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader.xhtml#ab708c11aea0f419821cd053e3e7dae89">  328</a></span>&#160;<a class="code" href="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader.xhtml#ab708c11aea0f419821cd053e3e7dae89">NumPyBinLoader::NumPyBinLoader</a>(std::string filename)</div><div class="line"><a name="l00329"></a><span class="lineno">  329</span>&#160;    : _filename(std::move(filename))</div><div class="line"><a name="l00330"></a><span class="lineno">  330</span>&#160;{</div><div class="line"><a name="l00331"></a><span class="lineno">  331</span>&#160;}</div><div class="line"><a name="l00332"></a><span class="lineno">  332</span>&#160;</div><div class="line"><a name="l00333"></a><span class="lineno"><a class="line" href="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader.xhtml#ab469d593b4bc92e1d1132a03de0aedca">  333</a></span>&#160;<span class="keywordtype">bool</span> <a class="code" href="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader.xhtml#ab469d593b4bc92e1d1132a03de0aedca">NumPyBinLoader::access_tensor</a>(<a class="code" href="classarm__compute_1_1_i_tensor.xhtml">ITensor</a> &amp;tensor)</div><div class="line"><a name="l00334"></a><span class="lineno">  334</span>&#160;{</div><div class="line"><a name="l00335"></a><span class="lineno">  335</span>&#160;    <span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_tensor_shape.xhtml">TensorShape</a>          tensor_shape = tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">tensor_shape</a>();</div><div class="line"><a name="l00336"></a><span class="lineno">  336</span>&#160;    std::vector&lt;unsigned long&gt; <a class="code" href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">shape</a>;</div><div class="line"><a name="l00337"></a><span class="lineno">  337</span>&#160;</div><div class="line"><a name="l00338"></a><span class="lineno">  338</span>&#160;    <span class="comment">// Open file</span></div><div class="line"><a name="l00339"></a><span class="lineno">  339</span>&#160;    std::ifstream stream(_filename, std::ios::in | std::ios::binary);</div><div class="line"><a name="l00340"></a><span class="lineno">  340</span>&#160;    <a class="code" href="core_2_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(!stream.good(), <span class="stringliteral">&quot;Failed to load binary data&quot;</span>);</div><div class="line"><a name="l00341"></a><span class="lineno">  341</span>&#160;    std::string <a class="code" href="hwc_8hpp.xhtml#a9d9174de5edba1e56fbfd90dc5e60f75">header</a> = npy::read_header(stream);</div><div class="line"><a name="l00342"></a><span class="lineno">  342</span>&#160;</div><div class="line"><a name="l00343"></a><span class="lineno">  343</span>&#160;    <span class="comment">// Parse header</span></div><div class="line"><a name="l00344"></a><span class="lineno">  344</span>&#160;    <span class="keywordtype">bool</span>        fortran_order = <span class="keyword">false</span>;</div><div class="line"><a name="l00345"></a><span class="lineno">  345</span>&#160;    std::string typestr;</div><div class="line"><a name="l00346"></a><span class="lineno">  346</span>&#160;    npy::parse_header(header, typestr, fortran_order, shape);</div><div class="line"><a name="l00347"></a><span class="lineno">  347</span>&#160;</div><div class="line"><a name="l00348"></a><span class="lineno">  348</span>&#160;    <span class="comment">// Check if the typestring matches the given one</span></div><div class="line"><a name="l00349"></a><span class="lineno">  349</span>&#160;    std::string expect_typestr = <a class="code" href="namespacearm__compute_1_1utils.xhtml#a7990fd2b875e2f6d4c1eded54539cb19">arm_compute::utils::get_typestring</a>(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">data_type</a>());</div><div class="line"><a name="l00350"></a><span class="lineno">  350</span>&#160;    <a class="code" href="core_2_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a>(typestr != expect_typestr, <span class="stringliteral">&quot;Typestrings mismatch&quot;</span>);</div><div class="line"><a name="l00351"></a><span class="lineno">  351</span>&#160;</div><div class="line"><a name="l00352"></a><span class="lineno">  352</span>&#160;    <span class="comment">// Reverse vector in case of non fortran order</span></div><div class="line"><a name="l00353"></a><span class="lineno">  353</span>&#160;    <span class="keywordflow">if</span>(!fortran_order)</div><div class="line"><a name="l00354"></a><span class="lineno">  354</span>&#160;    {</div><div class="line"><a name="l00355"></a><span class="lineno">  355</span>&#160;        std::reverse(shape.begin(), shape.end());</div><div class="line"><a name="l00356"></a><span class="lineno">  356</span>&#160;    }</div><div class="line"><a name="l00357"></a><span class="lineno">  357</span>&#160;</div><div class="line"><a name="l00358"></a><span class="lineno">  358</span>&#160;    <span class="comment">// Correct dimensions (Needs to match TensorShape dimension corrections)</span></div><div class="line"><a name="l00359"></a><span class="lineno">  359</span>&#160;    <span class="keywordflow">if</span>(shape.size() != tensor_shape.<a class="code" href="classarm__compute_1_1_dimensions.xhtml#a0f59f175e7682c7ed5f4ea30ef687834">num_dimensions</a>())</div><div class="line"><a name="l00360"></a><span class="lineno">  360</span>&#160;    {</div><div class="line"><a name="l00361"></a><span class="lineno">  361</span>&#160;        <span class="keywordflow">for</span>(<span class="keywordtype">int</span> i = static_cast&lt;int&gt;(shape.size()) - 1; i &gt; 0; --i)</div><div class="line"><a name="l00362"></a><span class="lineno">  362</span>&#160;        {</div><div class="line"><a name="l00363"></a><span class="lineno">  363</span>&#160;            <span class="keywordflow">if</span>(shape[i] == 1)</div><div class="line"><a name="l00364"></a><span class="lineno">  364</span>&#160;            {</div><div class="line"><a name="l00365"></a><span class="lineno">  365</span>&#160;                shape.pop_back();</div><div class="line"><a name="l00366"></a><span class="lineno">  366</span>&#160;            }</div><div class="line"><a name="l00367"></a><span class="lineno">  367</span>&#160;            <span class="keywordflow">else</span></div><div class="line"><a name="l00368"></a><span class="lineno">  368</span>&#160;            {</div><div class="line"><a name="l00369"></a><span class="lineno">  369</span>&#160;                <span class="keywordflow">break</span>;</div><div class="line"><a name="l00370"></a><span class="lineno">  370</span>&#160;            }</div><div class="line"><a name="l00371"></a><span class="lineno">  371</span>&#160;        }</div><div class="line"><a name="l00372"></a><span class="lineno">  372</span>&#160;    }</div><div class="line"><a name="l00373"></a><span class="lineno">  373</span>&#160;</div><div class="line"><a name="l00374"></a><span class="lineno">  374</span>&#160; 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   {</div><div class="line"><a name="l00386"></a><span class="lineno">  386</span>&#160;        <span class="comment">// If tensor has no padding read directly from stream.</span></div><div class="line"><a name="l00387"></a><span class="lineno">  387</span>&#160;        stream.read(reinterpret_cast&lt;char *&gt;(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#ab988210662dbd3bf32fd563c7dd1bdbf">buffer</a>()), tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">total_size</a>());</div><div class="line"><a name="l00388"></a><span class="lineno">  388</span>&#160;    }</div><div class="line"><a name="l00389"></a><span class="lineno">  389</span>&#160;    <span class="keywordflow">else</span></div><div class="line"><a name="l00390"></a><span class="lineno">  390</span>&#160;    {</div><div class="line"><a name="l00391"></a><span class="lineno">  391</span>&#160;        <span class="comment">// If tensor has padding accessing tensor elements through execution window.</span></div><div class="line"><a name="l00392"></a><span class="lineno">  392</span>&#160;        <a class="code" href="classarm__compute_1_1_window.xhtml">Window</a> window;</div><div class="line"><a name="l00393"></a><span class="lineno">  393</span>&#160;        window.<a class="code" href="classarm__compute_1_1_window.xhtml#a14470b4cb59140a1b6ff3b8f16c89ab6">use_tensor_dimensions</a>(tensor_shape);</div><div class="line"><a name="l00394"></a><span class="lineno">  394</span>&#160;</div><div class="line"><a name="l00395"></a><span class="lineno">  395</span>&#160;        <a class="code" href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">execute_window_loop</a>(window, [&amp;](<span class="keyword">const</span> <a class="code" href="classarm__compute_1_1_coordinates.xhtml">Coordinates</a> &amp; <span class="keywordtype">id</span>)</div><div class="line"><a name="l00396"></a><span class="lineno">  396</span>&#160;        {</div><div class="line"><a name="l00397"></a><span class="lineno">  397</span>&#160;            stream.read(reinterpret_cast&lt;char *&gt;(tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a48c7a05cc63f541d732250e39339cee2">ptr_to_element</a>(<span class="keywordtype">id</span>)), tensor.<a class="code" href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">info</a>()-&gt;<a class="code" href="classarm__compute_1_1_i_tensor_info.xhtml#aa459796b5489eca8a9160cb5dcf1a103">element_size</a>());</div><div class="line"><a name="l00398"></a><span class="lineno">  398</span>&#160;        });</div><div class="line"><a name="l00399"></a><span class="lineno">  399</span>&#160;    }</div><div class="line"><a name="l00400"></a><span class="lineno">  400</span>&#160;    <span class="keywordflow">return</span> <span class="keyword">true</span>;</div><div class="line"><a name="l00401"></a><span class="lineno">  401</span>&#160;}</div><div class="ttc" id="classarm__compute_1_1utils_1_1_p_p_m_loader_xhtml_aa420a28166e708e3f8b9ecc8e527fc09"><div class="ttname"><a href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#aa420a28166e708e3f8b9ecc8e527fc09">arm_compute::utils::PPMLoader::height</a></div><div class="ttdeci">unsigned int height() const </div><div class="ttdoc">Return the height of the currently open PPM file. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00482">Utils.h:482</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1utils_xhtml_a301d0b7bfd70f73fc1924f4281938d08"><div class="ttname"><a href="namespacearm__compute_1_1utils.xhtml#a301d0b7bfd70f73fc1924f4281938d08">arm_compute::utils::save_to_ppm</a></div><div class="ttdeci">void save_to_ppm(T &amp;tensor, const std::string &amp;ppm_filename)</div><div class="ttdoc">Template helper function to save a tensor image to a PPM file. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00655">Utils.h:655</a></div></div>
<div class="ttc" id="structarm__compute_1_1_border_size_xhtml_adffbf97e7b8b64e7cf32f0254cddf3c4"><div class="ttname"><a href="structarm__compute_1_1_border_size.xhtml#adffbf97e7b8b64e7cf32f0254cddf3c4">arm_compute::BorderSize::empty</a></div><div class="ttdeci">constexpr bool empty() const </div><div class="ttdoc">Check if the entire border is zero. </div><div class="ttdef"><b>Definition:</b> <a href="arm__compute_2core_2_types_8h_source.xhtml#l00256">Types.h:256</a></div></div>
<div class="ttc" id="classarm__compute_1_1_pixel_value_xhtml"><div class="ttname"><a href="classarm__compute_1_1_pixel_value.xhtml">arm_compute::PixelValue</a></div><div class="ttdoc">Class describing the value of a pixel for any image format. </div><div class="ttdef"><b>Definition:</b> <a href="_pixel_value_8h_source.xhtml#l00034">PixelValue.h:34</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a48d877702a2957f5a932c43a357866f9"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a48d877702a2957f5a932c43a357866f9">arm_compute::DataType::QS16</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a45cde9abb508c62d67c3bb2b9bf566a5"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a45cde9abb508c62d67c3bb2b9bf566a5">arm_compute::test::validation::shape</a></div><div class="ttdeci">shape</div><div class="ttdef"><b>Definition:</b> <a href="_c_l_2_convolution_8cpp_source.xhtml#l00133">Convolution.cpp:133</a></div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_top_n_predictions_accessor_xhtml_ab469d593b4bc92e1d1132a03de0aedca"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_top_n_predictions_accessor.xhtml#ab469d593b4bc92e1d1132a03de0aedca">arm_compute::graph_utils::TopNPredictionsAccessor::access_tensor</a></div><div class="ttdeci">bool access_tensor(ITensor &amp;tensor) override</div><div class="ttdoc">Interface to be implemented to access a given tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00198">GraphUtils.cpp:198</a></div></div>
<div class="ttc" id="classarm__compute_1_1_tensor_shape_xhtml"><div class="ttname"><a href="classarm__compute_1_1_tensor_shape.xhtml">arm_compute::TensorShape</a></div><div class="ttdoc">Shape of a tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_tensor_shape_8h_source.xhtml#l00039">TensorShape.h:39</a></div></div>
<div class="ttc" id="hwc_8hpp_xhtml_a9d9174de5edba1e56fbfd90dc5e60f75"><div class="ttname"><a href="hwc_8hpp.xhtml#a9d9174de5edba1e56fbfd90dc5e60f75">header</a></div><div class="ttdeci">union kbase_uk_hwcnt_header header</div><div class="ttdef"><b>Definition:</b> <a href="hwc_8hpp_source.xhtml#l00269">hwc.hpp:269</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a11cde4d3551db3f9498d339a67189543"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a11cde4d3551db3f9498d339a67189543">arm_compute::DataType::QS8</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_aac40b7097f2bda9274ae07fa33d15a79"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#aac40b7097f2bda9274ae07fa33d15a79">arm_compute::test::validation::a</a></div><div class="ttdeci">CLTensor a</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_g_e_m_m_8cpp_source.xhtml#l00121">GEMM.cpp:121</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a178f0d3d87f959e00a743328d95359d2"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a178f0d3d87f959e00a743328d95359d2">arm_compute::ITensorInfo::dimension</a></div><div class="ttdeci">virtual size_t dimension(size_t index) const =0</div><div class="ttdoc">Return the size of the requested dimension. </div></div>
<div class="ttc" id="utils_2_utils_8h_xhtml"><div class="ttname"><a href="utils_2_utils_8h.xhtml">Utils.h</a></div></div>
<div class="ttc" id="core_2_error_8h_xhtml_a54a6080c9f4df1f908e57a9bbb46f5da"><div class="ttname"><a href="core_2_error_8h.xhtml#a54a6080c9f4df1f908e57a9bbb46f5da">ARM_COMPUTE_ERROR_ON</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON(cond)</div><div class="ttdoc">If the condition is true then an error message is printed and an exception thrown. </div><div class="ttdef"><b>Definition:</b> <a href="core_2_error_8h_source.xhtml#l00306">Error.h:306</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6669348b484e3008dca2bfa8e85e40b5">arm_compute::Format::U8</a></div><div class="ttdoc">1 channel, 1 U8 per channel </div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7cfb31af63202568efef5214acfbf3ba"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7cfb31af63202568efef5214acfbf3ba">arm_compute::ITensorInfo::data_type</a></div><div class="ttdeci">virtual DataType data_type() const =0</div><div class="ttdoc">Data type used for each element of the tensor. </div></div>
<div class="ttc" id="_c_l_tensor_8h_xhtml"><div class="ttname"><a href="_c_l_tensor_8h.xhtml">CLTensor.h</a></div></div>
<div class="ttc" id="core_2_error_8h_xhtml_a05b19c75afe9c24200a62b9724734bbd"><div class="ttname"><a href="core_2_error_8h.xhtml#a05b19c75afe9c24200a62b9724734bbd">ARM_COMPUTE_ERROR</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR(...)</div><div class="ttdoc">Print the given message then throw an std::runtime_error. </div><div class="ttdef"><b>Definition:</b> <a href="core_2_error_8h_source.xhtml#l00238">Error.h:238</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a44ad4ef5a76e6aa6fb3e3fa079a54fda">arm_compute::Format::F32</a></div><div class="ttdoc">1 channel, 1 F32 per channel </div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader_xhtml_ab469d593b4bc92e1d1132a03de0aedca"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader.xhtml#ab469d593b4bc92e1d1132a03de0aedca">arm_compute::graph_utils::NumPyBinLoader::access_tensor</a></div><div class="ttdeci">bool access_tensor(ITensor &amp;tensor) override</div><div class="ttdoc">Interface to be implemented to access a given tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00333">GraphUtils.cpp:333</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_xhtml_a28edc8880596d14c099f3c2509efc8b3"><div class="ttname"><a href="namespacearm__compute_1_1test.xhtml#a28edc8880596d14c099f3c2509efc8b3">arm_compute::test::swap</a></div><div class="ttdeci">void swap(SimpleTensor&lt; U &gt; &amp;tensor1, SimpleTensor&lt; U &gt; &amp;tensor2)</div><div class="ttdef"><b>Definition:</b> <a href="_simple_tensor_8h_source.xhtml#l00367">SimpleTensor.h:367</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aef9ef3ebca4d2b64b6ec83808bafa5f2">arm_compute::Format::U16</a></div><div class="ttdoc">1 channel, 1 U16 per channel </div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_caffe_preproccessor_xhtml_a1545d087d050b8e9733e7e212df73666"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_caffe_preproccessor.xhtml#a1545d087d050b8e9733e7e212df73666">arm_compute::graph_utils::CaffePreproccessor::preprocess</a></div><div class="ttdeci">void preprocess(ITensor &amp;tensor) override</div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00062">GraphUtils.cpp:62</a></div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_random_accessor_xhtml_a47e2e3f731e842dde7baaf69634a9530"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_random_accessor.xhtml#a47e2e3f731e842dde7baaf69634a9530">arm_compute::graph_utils::RandomAccessor::RandomAccessor</a></div><div class="ttdeci">RandomAccessor(PixelValue lower, PixelValue upper, const std::random_device::result_type seed=0)</div><div class="ttdoc">Constructor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00218">GraphUtils.cpp:218</a></div></div>
<div class="ttc" id="helpers_8h_xhtml_a009469e4d9b8fce3b6d5e97d2077827d"><div class="ttname"><a href="helpers_8h.xhtml#a009469e4d9b8fce3b6d5e97d2077827d">offset</a></div><div class="ttdeci">__global uchar * offset(const Image *img, int x, int y)</div><div class="ttdoc">Get the pointer position of a Image. </div><div class="ttdef"><b>Definition:</b> <a href="helpers_8h_source.xhtml#l00301">helpers.h:301</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml">arm_compute::ITensor</a></div><div class="ttdoc">Interface for NEON tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_8h_source.xhtml#l00036">ITensor.h:36</a></div></div>
<div class="ttc" id="core_2_error_8h_xhtml_a4103adbb45806b2f2002d44b91d0d206"><div class="ttname"><a href="core_2_error_8h.xhtml#a4103adbb45806b2f2002d44b91d0d206">ARM_COMPUTE_UNUSED</a></div><div class="ttdeci">#define ARM_COMPUTE_UNUSED(var)</div><div class="ttdoc">To avoid unused variables warnings. </div><div class="ttdef"><b>Definition:</b> <a href="core_2_error_8h_source.xhtml#l00147">Error.h:147</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml_a14470b4cb59140a1b6ff3b8f16c89ab6"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml#a14470b4cb59140a1b6ff3b8f16c89ab6">arm_compute::Window::use_tensor_dimensions</a></div><div class="ttdeci">void use_tensor_dimensions(const TensorShape &amp;shape, size_t first_dimension=Window::DimX)</div><div class="ttdoc">Use the tensor&amp;#39;s dimensions to fill the window dimensions. </div><div class="ttdef"><b>Definition:</b> <a href="_window_8inl_source.xhtml#l00240">Window.inl:240</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a56d8353718e6fdc78b8d69078a2cdb94">arm_compute::Format::F16</a></div><div class="ttdoc">1 channel, 1 F16 per channel </div></div>
<div class="ttc" id="hwc_8hpp_xhtml_a4fef07ab304fc672e0407e7598fb1870"><div class="ttname"><a href="hwc_8hpp.xhtml#a4fef07ab304fc672e0407e7598fb1870">ret</a></div><div class="ttdeci">uint32_t ret</div><div class="ttdef"><b>Definition:</b> <a href="hwc_8hpp_source.xhtml#l00261">hwc.hpp:261</a></div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_p_p_m_accessor_xhtml_a0d3c4a4f52edede1f0a6d31a8f0b4ffb"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_p_p_m_accessor.xhtml#a0d3c4a4f52edede1f0a6d31a8f0b4ffb">arm_compute::graph_utils::PPMAccessor::PPMAccessor</a></div><div class="ttdeci">PPMAccessor(std::string ppm_path, bool bgr=true, std::unique_ptr&lt; IPreprocessor &gt; preprocessor=nullptr)</div><div class="ttdoc">Constructor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00114">GraphUtils.cpp:114</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58aa1e28eee0339658d39a8b4d325b56e9c">arm_compute::Format::S32</a></div><div class="ttdoc">1 channel, 1 S32 per channel </div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a115dca124dc6423c7a400b8a8a0270cc"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a115dca124dc6423c7a400b8a8a0270cc">arm_compute::DataType::S64</a></div></div>
<div class="ttc" id="classarm__compute_1_1_sub_tensor_xhtml"><div class="ttname"><a href="classarm__compute_1_1_sub_tensor.xhtml">arm_compute::SubTensor</a></div><div class="ttdoc">Basic implementation of the sub-tensor interface. </div><div class="ttdef"><b>Definition:</b> <a href="runtime_2_sub_tensor_8h_source.xhtml#l00037">SubTensor.h:37</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1utils_xhtml_a7990fd2b875e2f6d4c1eded54539cb19"><div class="ttname"><a href="namespacearm__compute_1_1utils.xhtml#a7990fd2b875e2f6d4c1eded54539cb19">arm_compute::utils::get_typestring</a></div><div class="ttdeci">std::string get_typestring(DataType data_type)</div><div class="ttdoc">Obtain numpy type string from DataType. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00122">Utils.h:122</a></div></div>
<div class="ttc" id="classarm__compute_1_1_pixel_value_xhtml_a3997ae7153b94a3595d1a33186356a5b"><div class="ttname"><a href="classarm__compute_1_1_pixel_value.xhtml#a3997ae7153b94a3595d1a33186356a5b">arm_compute::PixelValue::get</a></div><div class="ttdeci">void get(uint8_t &amp;v) const </div><div class="ttdoc">Interpret the pixel value as a U8. </div><div class="ttdef"><b>Definition:</b> <a href="_pixel_value_8h_source.xhtml#l00157">PixelValue.h:157</a></div></div>
<div class="ttc" id="classarm__compute_1_1utils_1_1_p_p_m_loader_xhtml_a36e58f3e64f3851ebac7a9556b4704ed"><div class="ttname"><a href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a36e58f3e64f3851ebac7a9556b4704ed">arm_compute::utils::PPMLoader::open</a></div><div class="ttdeci">void open(const std::string &amp;ppm_filename)</div><div class="ttdoc">Open a PPM file and reads its metadata (Width, height) </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00264">Utils.h:264</a></div></div>
<div class="ttc" id="_graph_utils_8h_xhtml"><div class="ttname"><a href="_graph_utils_8h.xhtml">GraphUtils.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_random_accessor_xhtml_ab469d593b4bc92e1d1132a03de0aedca"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_random_accessor.xhtml#ab469d593b4bc92e1d1132a03de0aedca">arm_compute::graph_utils::RandomAccessor::access_tensor</a></div><div class="ttdeci">bool access_tensor(ITensor &amp;tensor) override</div><div class="ttdoc">Interface to be implemented to access a given tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00250">GraphUtils.cpp:250</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a48c7a05cc63f541d732250e39339cee2"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a48c7a05cc63f541d732250e39339cee2">arm_compute::ITensor::ptr_to_element</a></div><div class="ttdeci">uint8_t * ptr_to_element(const Coordinates &amp;id) const </div><div class="ttdoc">Return a pointer to the element at the passed coordinates. </div><div class="ttdef"><b>Definition:</b> <a href="_i_tensor_8h_source.xhtml#l00063">ITensor.h:63</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58ac8bd5bedff8ef192d39a962afc0e19ee">arm_compute::Format::U32</a></div><div class="ttdoc">1 channel, 1 U32 per channel </div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a7c66505457d00ece3aa4b34cab80757d"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a7c66505457d00ece3aa4b34cab80757d">arm_compute::ITensorInfo::tensor_shape</a></div><div class="ttdeci">virtual const TensorShape &amp; tensor_shape() const =0</div><div class="ttdoc">Size for each dimension of the tensor. </div></div>
<div class="ttc" id="namespacearm__compute_xhtml_a6c0dcc38187027dcb89cd9724bc5a823"><div class="ttname"><a href="namespacearm__compute.xhtml#a6c0dcc38187027dcb89cd9724bc5a823">arm_compute::execute_window_loop</a></div><div class="ttdeci">void execute_window_loop(const Window &amp;w, L &amp;&amp;lambda_function, Ts &amp;&amp;...iterators)</div><div class="ttdoc">Iterate through the passed window, automatically adjusting the iterators and calling the lambda_funct...</div><div class="ttdef"><b>Definition:</b> <a href="_helpers_8inl_source.xhtml#l00122">Helpers.inl:122</a></div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_caffe_preproccessor_xhtml_a60e1354276a6ffd7359634e1ab464cff"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_caffe_preproccessor.xhtml#a60e1354276a6ffd7359634e1ab464cff">arm_compute::graph_utils::CaffePreproccessor::CaffePreproccessor</a></div><div class="ttdeci">CaffePreproccessor(std::array&lt; float, 3 &gt; mean=std::array&lt; float, 3 &gt;{{0, 0, 0}}, bool bgr=true)</div><div class="ttdoc">Default Constructor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00053">GraphUtils.cpp:53</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6af14462d71aa842202c3e4b272c7ec924">arm_compute::DataType::QASYMM8</a></div></div>
<div class="ttc" id="classarm__compute_1_1_coordinates_xhtml"><div class="ttname"><a href="classarm__compute_1_1_coordinates.xhtml">arm_compute::Coordinates</a></div><div class="ttdoc">Coordinates of an item. </div><div class="ttdef"><b>Definition:</b> <a href="_coordinates_8h_source.xhtml#l00037">Coordinates.h:37</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_ab988210662dbd3bf32fd563c7dd1bdbf"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#ab988210662dbd3bf32fd563c7dd1bdbf">arm_compute::ITensor::buffer</a></div><div class="ttdeci">virtual uint8_t * buffer() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return a pointer to CPU memory. ...</div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_xhtml_a0e95dc1e53c361348314873b168ae237"><div class="ttname"><a href="classarm__compute_1_1_i_tensor.xhtml#a0e95dc1e53c361348314873b168ae237">arm_compute::ITensor::info</a></div><div class="ttdeci">virtual ITensorInfo * info() const =0</div><div class="ttdoc">Interface to be implemented by the child class to return the tensor&amp;#39;s metadata. </div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_aa459796b5489eca8a9160cb5dcf1a103"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#aa459796b5489eca8a9160cb5dcf1a103">arm_compute::ITensorInfo::element_size</a></div><div class="ttdeci">virtual size_t element_size() const =0</div><div class="ttdoc">Element size in bytes calculated as data_size() * num_channels() </div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader_xhtml_ab708c11aea0f419821cd053e3e7dae89"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_num_py_bin_loader.xhtml#ab708c11aea0f419821cd053e3e7dae89">arm_compute::graph_utils::NumPyBinLoader::NumPyBinLoader</a></div><div class="ttdeci">NumPyBinLoader(std::string filename)</div><div class="ttdoc">Default Constructor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00328">GraphUtils.cpp:328</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a07b929c34ad1dc823d8315876aa403ce"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a07b929c34ad1dc823d8315876aa403ce">arm_compute::ITensorInfo::padding</a></div><div class="ttdeci">virtual PaddingSize padding() const =0</div><div class="ttdoc">Padding of tensor. </div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c"><div class="ttname"><a href="namespacearm__compute.xhtml#ab4e88c89b3b7ea1735996cc4def22d58a6e0b0886efb94aec797f6b830329b72c">arm_compute::Format::S16</a></div><div class="ttdoc">1 channel, 1 S16 per channel </div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_top_n_predictions_accessor_xhtml_ad12f4e3c945ec4fad9ab6386954a3550"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_top_n_predictions_accessor.xhtml#ad12f4e3c945ec4fad9ab6386954a3550">arm_compute::graph_utils::TopNPredictionsAccessor::TopNPredictionsAccessor</a></div><div class="ttdeci">TopNPredictionsAccessor(const std::string &amp;labels_path, size_t top_n=5, std::ostream &amp;output_stream=std::cout)</div><div class="ttdoc">Constructor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00141">GraphUtils.cpp:141</a></div></div>
<div class="ttc" id="_validate_8h_xhtml_aadf5c9cff86327b96d88d04649d9715e"><div class="ttname"><a href="_validate_8h.xhtml#aadf5c9cff86327b96d88d04649d9715e">ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(t, c,...)</div><div class="ttdef"><b>Definition:</b> <a href="_validate_8h_source.xhtml#l00701">Validate.h:701</a></div></div>
<div class="ttc" id="hwc_8hpp_xhtml_a0f61d63b009d0880a89c843bd50d8d76"><div class="ttname"><a href="hwc_8hpp.xhtml#a0f61d63b009d0880a89c843bd50d8d76">value</a></div><div class="ttdeci">void * value</div><div class="ttdef"><b>Definition:</b> <a href="hwc_8hpp_source.xhtml#l00278">hwc.hpp:278</a></div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_p_p_m_accessor_xhtml_ab469d593b4bc92e1d1132a03de0aedca"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_p_p_m_accessor.xhtml#ab469d593b4bc92e1d1132a03de0aedca">arm_compute::graph_utils::PPMAccessor::access_tensor</a></div><div class="ttdeci">bool access_tensor(ITensor &amp;tensor) override</div><div class="ttdoc">Interface to be implemented to access a given tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00119">GraphUtils.cpp:119</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_ad0bd5cc32e7e4c0699eccba91e5de397"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#ad0bd5cc32e7e4c0699eccba91e5de397">arm_compute::ITensorInfo::offset_first_element_in_bytes</a></div><div class="ttdeci">virtual size_t offset_first_element_in_bytes() const =0</div><div class="ttdoc">The offset from the beginning of the memory allocation to the first element of the tensor...</div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_t_f_preproccessor_xhtml_a1545d087d050b8e9733e7e212df73666"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_t_f_preproccessor.xhtml#a1545d087d050b8e9733e7e212df73666">arm_compute::graph_utils::TFPreproccessor::preprocess</a></div><div class="ttdeci">void preprocess(ITensor &amp;tensor) override</div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00039">GraphUtils.cpp:39</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1graph__utils_xhtml"><div class="ttname"><a href="namespacearm__compute_1_1graph__utils.xhtml">arm_compute::graph_utils</a></div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8h_source.xhtml#l00039">GraphUtils.h:39</a></div></div>
<div class="ttc" id="classarm__compute_1_1_i_tensor_info_xhtml_a18064e0011c3869d884653e9e7c47b66"><div class="ttname"><a href="classarm__compute_1_1_i_tensor_info.xhtml#a18064e0011c3869d884653e9e7c47b66">arm_compute::ITensorInfo::total_size</a></div><div class="ttdeci">virtual size_t total_size() const =0</div><div class="ttdoc">Returns the total size of the tensor in bytes. </div></div>
<div class="ttc" id="classarm__compute_1_1_dimensions_xhtml_a0f59f175e7682c7ed5f4ea30ef687834"><div class="ttname"><a href="classarm__compute_1_1_dimensions.xhtml#a0f59f175e7682c7ed5f4ea30ef687834">arm_compute::Dimensions::num_dimensions</a></div><div class="ttdeci">unsigned int num_dimensions() const </div><div class="ttdoc">Returns the effective dimensionality of the tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_dimensions_8h_source.xhtml#l00122">Dimensions.h:122</a></div></div>
<div class="ttc" id="core_2_error_8h_xhtml_a5bbdcf574d3f5e412fa6a1117911e67b"><div class="ttname"><a href="core_2_error_8h.xhtml#a5bbdcf574d3f5e412fa6a1117911e67b">ARM_COMPUTE_ERROR_ON_MSG</a></div><div class="ttdeci">#define ARM_COMPUTE_ERROR_ON_MSG(cond,...)</div><div class="ttdef"><b>Definition:</b> <a href="core_2_error_8h_source.xhtml#l00297">Error.h:297</a></div></div>
<div class="ttc" id="classarm__compute_1_1utils_1_1_p_p_m_loader_xhtml_a7c3f70e1caee95bb95c62346e130e5ab"><div class="ttname"><a href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a7c3f70e1caee95bb95c62346e130e5ab">arm_compute::utils::PPMLoader::fill_planar_tensor</a></div><div class="ttdeci">void fill_planar_tensor(T &amp;tensor, bool bgr=false)</div><div class="ttdoc">Fill a tensor with 3 planes (one for each channel) with the content of the currently open PPM file...</div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00399">Utils.h:399</a></div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_p_p_m_writer_xhtml_ab469d593b4bc92e1d1132a03de0aedca"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_p_p_m_writer.xhtml#ab469d593b4bc92e1d1132a03de0aedca">arm_compute::graph_utils::PPMWriter::access_tensor</a></div><div class="ttdeci">bool access_tensor(ITensor &amp;tensor) override</div><div class="ttdoc">Interface to be implemented to access a given tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00079">GraphUtils.cpp:79</a></div></div>
<div class="ttc" id="runtime_2_sub_tensor_8h_xhtml"><div class="ttname"><a href="runtime_2_sub_tensor_8h.xhtml">SubTensor.h</a></div></div>
<div class="ttc" id="_open_c_l_8h_xhtml"><div class="ttname"><a href="_open_c_l_8h.xhtml">OpenCL.h</a></div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_dummy_accessor_xhtml_ac5ae9597ba20e5581726743fe7c154b5"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_dummy_accessor.xhtml#ac5ae9597ba20e5581726743fe7c154b5">arm_compute::graph_utils::DummyAccessor::DummyAccessor</a></div><div class="ttdeci">DummyAccessor(unsigned int maximum=1)</div><div class="ttdoc">Constructor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00094">GraphUtils.cpp:94</a></div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_p_p_m_writer_xhtml_a9ea94bf5b7d00ddb836df1b8dcedb93a"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_p_p_m_writer.xhtml#a9ea94bf5b7d00ddb836df1b8dcedb93a">arm_compute::graph_utils::PPMWriter::PPMWriter</a></div><div class="ttdeci">PPMWriter(std::string name, unsigned int maximum=1)</div><div class="ttdoc">Constructor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00074">GraphUtils.cpp:74</a></div></div>
<div class="ttc" id="classarm__compute_1_1graph__utils_1_1_dummy_accessor_xhtml_ab469d593b4bc92e1d1132a03de0aedca"><div class="ttname"><a href="classarm__compute_1_1graph__utils_1_1_dummy_accessor.xhtml#ab469d593b4bc92e1d1132a03de0aedca">arm_compute::graph_utils::DummyAccessor::access_tensor</a></div><div class="ttdeci">bool access_tensor(ITensor &amp;tensor) override</div><div class="ttdoc">Interface to be implemented to access a given tensor. </div><div class="ttdef"><b>Definition:</b> <a href="_graph_utils_8cpp_source.xhtml#l00099">GraphUtils.cpp:99</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a1ad5f6f3069070ec4cbbdc94d5e61e0e"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a1ad5f6f3069070ec4cbbdc94d5e61e0e">arm_compute::DataType::F64</a></div></div>
<div class="ttc" id="classarm__compute_1_1utils_1_1_p_p_m_loader_xhtml_a7b736ec9a05be5c498760d35a0406ed3"><div class="ttname"><a href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml#a7b736ec9a05be5c498760d35a0406ed3">arm_compute::utils::PPMLoader::width</a></div><div class="ttdeci">unsigned int width() const </div><div class="ttdoc">Return the width of the currently open PPM file. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00475">Utils.h:475</a></div></div>
<div class="ttc" id="namespacearm__compute_1_1test_1_1validation_xhtml_a7b8004eef325a40dd43eb80755610fff"><div class="ttname"><a href="namespacearm__compute_1_1test_1_1validation.xhtml#a7b8004eef325a40dd43eb80755610fff">arm_compute::test::validation::b</a></div><div class="ttdeci">CLTensor b</div><div class="ttdef"><b>Definition:</b> <a href="validation_2_c_l_2_g_e_m_m_8cpp_source.xhtml#l00122">GEMM.cpp:122</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6a31d65cccd6593e4101db93fb878abcaa"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6a31d65cccd6593e4101db93fb878abcaa">arm_compute::DataType::U64</a></div></div>
<div class="ttc" id="namespacearm__compute_xhtml_ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975"><div class="ttname"><a href="namespacearm__compute.xhtml#ad8ed01ff3ff33333d8e19db4d2818bb6aafb0fced528eaac5fe170b763cda5975">arm_compute::DataType::S8</a></div></div>
<div class="ttc" id="classarm__compute_1_1_window_xhtml"><div class="ttname"><a href="classarm__compute_1_1_window.xhtml">arm_compute::Window</a></div><div class="ttdoc">Describe a multidimensional execution window. </div><div class="ttdef"><b>Definition:</b> <a href="_window_8h_source.xhtml#l00039">Window.h:39</a></div></div>
<div class="ttc" id="classarm__compute_1_1utils_1_1_p_p_m_loader_xhtml"><div class="ttname"><a href="classarm__compute_1_1utils_1_1_p_p_m_loader.xhtml">arm_compute::utils::PPMLoader</a></div><div class="ttdoc">Class to load the content of a PPM file into an Image. </div><div class="ttdef"><b>Definition:</b> <a href="utils_2_utils_8h_source.xhtml#l00253">Utils.h:253</a></div></div>
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